tbuckley/cabot-search huggingface dataset:
Comparison of publications between cancer sites in high impact factor journals.
Authors: Nikita Sinha, Amanda McDonald, Danika Barry, Emma Longley Barber
Journal: Journal of Clinical Oncology (2023)

1588 Background: Prior studies have shown disparities in federal funding allocation by cancer site after accounting for mortality, incidence, and person-years of life lost. Whether disparities exist in publications in high impact factor journals is unknown. The aim of this study is to analyze research publications in high impact factor journals by cancer site relative to their burden from 2000 to 2018. Methods: Abstracts from the top 55 impact factor journals from 2000 to 2018 were extracted from PubMed. We developed an algorithm to search the title of the abstract to determine whether the abstract was about cancer and identify the cancer type. The algorithm was validated against the gold standard of human review in 1143 abstracts and yielded a sensitivity and a specificity of &gt;95%. An article proportion for each cancer site was calculated (abstracts for a cancer site / total cancer abstracts). Article proportion was compared to cancer site-specific incidence, mortality and lethality from NCI’s SEER database using scatter plots and non-parametric Wilcoxon signed rank test. Results: We identified 128,377 articles; 31,045 (24%) were about cancer. Cancers with the most publications in high impact factor journals were breast (22%), lung (11%), and colorectal (10%) cancer. Breast, lung and colorectal cancer were also well represented in high impact factor journals compared to their incidence, mortality, and lethality. Gynecologic (ovarian, cervical, and endometrial), pancreatic, hepatobiliary, and prostate cancers were poorly represented in all 3 metrics. Breast, lung, and colorectal cancer ranked in the top half of Article to Lethality scores, while the gynecologic, pancreatic, and hepatobiliary cancers were in the bottom half (p &lt;0.05 for all comparisons). Comparison of rankings by lethality versus by funding indicates relative underfunding of the gynecologic, pancreatic, hepatobiliary, and prostate cancers. Conclusions: Research publications in high impact factor journals by cancer site are not proportionate to individual societal cancer burden. Significant disparities exist between breast, lung, and colorectal cancer when compared to gynecologic, pancreatic, hepatobiliary, and prostate cancers relative to their disease burden. Underfunding of these cancer sites likely contributes to this publication gap.[Table: see text]
Representativeness of patients with lung cancer in an integrated health care delivery system.
Authors: Mike Z. Yang, Raymond Liu, Julie Von Behren, Katherine Lin, Alyce S. Adams, Lawrence H. Kushi, Charles P. Quesenberry, Jeffrey B. Velotta, Kelly C. Young-Wolff, Scarlett L. Gomez, Salma Shariff-Marco, Lori C. Sakoda
Journal: Journal of Clinical Oncology (2023)

e13600 Background: Lung cancer is the leading cause of cancer death in the US, and research is critical to reducing its morbidity and mortality. Minoritized groups (e.g., low income) that face higher lung cancer burden are underrepresented in clinical trials, which are often conducted at NCI-designated cancer centers (NCICCs). Large integrated health systems such as Kaiser Permanente Northern California (KPNC) may be well-positioned to produce research findings that are more representative of patient populations in important clinical and demographic characteristics. In this study, we evaluated the representativeness of lung cancer patients from KPNC compared to those from NCICCs and non-NCICCs in Northern California. Methods: We extracted individual and neighborhood data from the California Cancer Registry, California Neighborhoods Data System, and CalEnviroScreen 4.0 for patients with invasive lung cancer diagnosed from 2015 through 2019 within the KPNC catchment area. We compared these characteristics among patients from KPNC, NCICCs (Stanford, UC Davis, UCSF), and all other non-NCICCs. Results: Of 27,288 patients, 31% are from KPNC, 8% from NCICCs, and 61% from other non-NCICCs (Table). KPNC patients are more similar to other non-NCICC patients and the total lung cancer population than to NCICC patients on most characteristics. KPNC patients are slightly older, more likely to be female, and less likely to be Asian American/Pacific Islander (AAPI), compared to other non-NCICC patients. In contrast, NCICC patients are younger, less likely to be female or non-AAPI minoritized racial and ethnic groups, and present with less stage IV disease and more adenocarcinoma at diagnosis. Both KPNC and NCICC patients are more likely to reside in neighborhoods with the highest socioeconomic status (SES) and lowest pollution burden than other non-NCICC patients. Given large numbers, all differences were statistically significant (p&lt;0.001). Conclusions: These analyses demonstrate that lung cancer patients in KPNC are more broadly representative of the overall lung cancer population than those in NCICCs, and can produce generalizable research findings to improve outcomes for all lung cancer patients. [Table: see text]
Trial eligibility criteria (EC) and diversity among patients with advanced non small cell lung cancer (advNSCLC).
Authors: Maneet Kaur, Filip Frahm, Mustafa Ascha, Jenny Guadamuz, Adam Gottesman, Barry Leybovich, Arjun Sondhi, Yihua Zhao, Neal J. Meropol, Trevor Joseph Royce
Journal: Journal of Clinical Oncology (2023)

1566 Background: FDA guidance encourages using real world data in developing diversity plans for clinical trials. Diversity plans may incorporate more inclusive (or expanded) EC, which may increase enrollment of minoritized populations. Whether broadened EC affect the diversity of eligible participants is unknown. Methods: Using the nationwide Flatiron Health electronic health record-derived deidentified database, we included patients with advNSCLC from 1/1/17-11/30/22 with a line of therapy (LOT) (N=61596). EC were defined by FDA, NCI/CTEP, and ASCO/FoCR standards, and included ECOG, ALT, AST, ALP, bilirubin, eGFR, CrCl, HGB, ANC &amp; PLT -90 to +7 days from first LOT. Claims-linkage identified brain mets (BM), congestive heart failure (CHF), hepatitis C (HCV) &amp; B (HBV), HIV and myocardial infarction (MI) within 6 months of first LOT. Logistic regression estimated odds ratios (OR) for exclusion by criterion associated with gender, age, race/ethnicity and area-level socioeconomic status (SES). Adjusting for clinical characteristics, Cox regression estimated hazard ratios (HR) for real world overall survival (rwOS). Results: Female patients (vs male patients) had greater odds of exclusion by CrCl (OR 2.9), eGFR (OR 1.27) &amp; BM (OR 1.30). Compared to non-Latinx (NL) White patients, NL Black patients had greater odds of exclusion by ECOG (OR 1.17), CrCl (OR 1.33), eGFR (OR 1.61), HGB (OR 2.2), ANC (OR 1.71), HIV (OR 5.31), CHF (OR 1.31), HBV (OR 2.29) and HCV (OR 2.73); NL Asian patients by ALT (OR 1.64), ALP (OR 1.71), CrCl (OR 1.63), BM (OR 1.45) and HBV (OR 26.2); and Latinx patients by ALP (OR 1.56), HIV (OR 2.23) and HCV (OR 1.47). Compared to younger patients (18-49), older patients (75-84) had greater odds of exclusion by ECOG (OR 2.12), bilirubin (OR 1.53), CrCl (OR 41.9), eGFR (OR 9.54), CHF (OR 4.9) and MI (OR 4.7). Patients with the lowest (vs highest) quintile of SES had greater odds of exclusion by ECOG (OR 1.29) and HGB (OR 1.52). Among patients with complete data on all non-claims criteria (N=22117), the impact of expanding EC on diversity is shown, except SES which was similar. Compared to standard EC, the group with expanded EC had lower rwOS (adj HR 1.32; 95% CI 1.28-1.37). Conclusions: Expanding EC has the potential to increase the proportion and absolute number of Black, older, and female patients in advNSCLC trials. The resulting more diverse eligible population may have different clinical outcomes compared to a cohort defined by more restrictive EC. Future work will explore generalizability of findings to other clinical contexts.[Table: see text]
Real-world, single-center experience on the outcomes of neoadjuvant chemotherapy and trastuzumab alone or in combination with pertuzumab in human epidermal growth factor receptor-2 breast cancer patients.
Authors: Ashok Kumar Vaid, Devender Sharma, Jyoti Wadhwa, Rajeev Kumar Agarwal, Kanchan Kaur, Shina Goyal, Dheeraj Gautam, Jyoti Arora, Sabhyata Gupta, Ruchika Goel, Ashok Sen
Journal: Journal of Clinical Oncology (2023)

e12589 Background: Neoadjuvant chemotherapy (NACT) is the standard of care for early-stage breast cancer (BC). Human epidermal growth factor receptor 2 (HER2) positive disease constitutes a large proportion of BC patients, and HER2 overexpression is associated with poor prognosis. The introduction of HER2+ targeted therapies, such as trastuzumab and pertuzumab, has resulted in improved outcomes in HER2+ BC. NACT in combination with HER2 targeted therapies aims at achieving pathological complete response (pCR) and an improved survival rates. Methods: We performed a retrospective review of HER2+ BC patients who were treated at Medanta – The Medicity Hospital, Gurugram, Haryana, India, between 2011 and 2021. A total of 108 HER2+ BC patients who received NACT with platinum, anthracycline or taxane-based regimens, along with trastuzumab alone or in combination with pertuzumab, were included. Results: Of 108 enrolled patients, 66 and 42 patients received neoadjuvant single-blockade (trastuzumab) and dual-blockade (trastuzumab and pertuzumab) anti-HER2 therapy, respectively. The majority of patients were aged &lt; 60 years. The patient populations were comparable in terms of clinical stage, hormone receptor status, histopathology category [Invasive ductal carcinoma (IDC) being most common] and Ki67 status for both groups. All patients had IHC3+/FISH+ HER2 expression. No significant (p = 0.896) difference was observed for breast conserving surgery between the groups. A higher pCR rate after surgery was reported in the dual-blockade versus single-blockade group (50% vs. 39.2%; p = 0.271). The median follow-up duration was 21.9 and 15.2 months in the single-blockade and dual-blockade groups, respectively. For dual- vs. single- blockade groups, the 1-year OS rates were 100% each, and 3-year OS rates were 100% vs. 98.48%. For dual- vs. single- blockade groups, the 1-year DFS rates were 100% vs. 95.45%, and 3-year DFS rates were 92.85% vs. 80.3% respectively. Conclusions: Neoadjuvant chemotherapy with dual HER2-blockade had higher pCR and survival rates compared with the single HER2-blockade strategy in HER2 positive breast cancer. [Table: see text]
Assessment of the differential profile of breast intratumoral bacteria in treatment responders and nonresponders.
Authors: Amedra Basgaran, Eva Lymberopoulos, Sophie Paschke, Michael Hobbs, Muhannad Alomari, Nikhil Sharma
Journal: Journal of Clinical Oncology (2023)

580 Background: Despite improvements in breast cancer therapy, many patients do not respond to treatment: the response rate varies between 31 and 80% [Walks et al., 2019]. The tumor microenvironment contains a microbiome which is both cancer type-specific and different to surrounding normal tissue [Nejman et al., 2020]. It plays an important role in tumour microenvironment crosstalk with tumor cells and has been implicated in disease pathogenesis, being recognised in the latest hallmarks of cancer [Hanahan et Weinberg, 2011]. It has also successfully predicted treatment response [Chen et al., 2022; Hermida et al., 2022]. Here, we use conventional microbiome analysis alongside our proprietary mechanistically-powered technology platform to compare the intratumoral bacteria between responders and non-responders. We hypothesise that there are significant differences between those groups regarding composition and mechanistic function of the bacteria. Methods: The tumor microbiome can be deduced from existing sequencing data of tumor biopsy samples. Using 34 tumor DNA samples from 5 breast cancer studies, we compared the intratumoral bacterial profiles of responders to non-responders of various treatments. We performed microbiome analysis in R, including alpha diversity, compositional abundance profiles, and PERMANOVA (permutational analysis of variance). Additionally, BioCorteX CarbonMirror version dated 2023-02-14 was used to infer mechanistic links between bacterial species and the up- and downregulation of genes implicated in the hallmarks of cancer. Results: The results show significant differences in diversity and compositional profile between responders and non-responders: Non-responders have significantly higher alpha diversity ( p&lt;0.05) and a higher proportion of Proteobacteria. PERMANOVA analysis revealed that while responders are more likely to have commensal bacteria, non-responder tumour microbiomes are more likely to harbor pathogenic species such as Mycoplasmopsis fermentans. Mechanistic analysis showed that for all responders the tumor microbiome is consistently promoting tumor suppressor genes and downregulating proto-oncogenes. In non-responders, however, the tumor microbiome is upregulating and downregulating both with unclear consistency. Conclusions: Our results show microbiome differences between responders and non-responders which were mechanistically implicated in tumor pathogenesis. Further analysis divided by the hallmarks of cancer is required to fully understand the non-responder microbiome links. The reported findings could make the tumor microbiome a useful biomarker aiding patient stratification for both prognosis and treatment choice. They also highlight a potentially meaningful mechanistic link between tumour microenvironment and treatment response that could be leveraged as a novel therapeutic avenue.
Correlation of neutrophil-to-lymphocyte ratio and stromal tumor infiltrating lymphocytes across early breast cancer subtypes.
Authors: Esmeralda García-Torralba, Alejandra Ivars-Rubio, Miguel Perez-Ramos, Esther Navarro Manzano, Noel Blaya-Boluda, Pilar de la Morena Barrio, Elisa Garcia-Garre, Gema Marin Zafra, Miguel Angel Moya Hernandez, Maria Esperanza Guirao Garcia, Asuncion Chaves Benito, Elena Garcia Martinez, Francisco Ayala
Journal: Journal of Clinical Oncology (2023)

e12558 Background: The tumor microenvironment plays a key role in the treatment response and prognosis of breast cancer (BC) patients, but the integrity of the peripheral immune system is also relevant. Understanding the biological correlation of immune-related prognostic factors, such as neutrophil-to-lymphocyte ratio (NLR) and stromal tumor infiltrating lymphocytes (sTIL), is necessary to improve its clinical applicability and the possible generation of more complex biomarkers that can direct treatment. Methods: Observational and single-center cohort of 1006 early BC patients (2009-2020). Pre-treatment NLR in peripheral blood and sTIL at diagnostic biopsy were determined. The correlation between NLR and sTIL (Spearman's Rho) overall and by subtypes, as well as its prognostic value for overall (OS) or disease-free survival (DFS) by Cox regression were evaluated. Results: NLR could be determined in 965 (96%) patients; in536 (53%) patients both NLR and sTIL were available. No statistical differences in baseline characteristics between both cohorts were found. Median age: 50 (range: 24-89); 93% infiltrating ductal carcinoma; 39.4% grade 3; 42.2% stage III; subtypes: hormone receptor (HR)+/HER2- (78.2%), HER2+/HR(+/-)(9.9%), triple negative breast cancer (TNBC) (11.9%); 70.5% treated with neoadjuvant chemotherapy. Median sTIL was 5% (SD: 16.2) with higher values in grade 3 (p &lt; 0.001), HR- (p &lt; 0.001) and HER2+ (p = 0.001). The median NLR was 1.95 (SD: 1.20), with no differences by subtype. There was no overall relationship between NLR and sTIL (ρ:0.32, p = 0.456). Correlation was also ruled out for each molecular subtype: HR+/HER2- (ρ:0.05, p = 0.301), HER2+/HR(+/-) (ρ:0.16, p = 0.251) and TNBC (ρ:0.21, p = 0.104). In a univariate predictive model for survival (N = 965), NLR showed prognostic value for DFS (HR 0.96, 95%CI: 0.80-1.17, p = 0.711) or OS (HR 1.02, 95%CI: 0.85-1.23, p = 0.798), neither in the whole group nor in the analysis by immunochemical subtypes. Conclusions: No correlation was observed between two of the most relevant biomarkers of immune activation in the tumor (sTIL) and peripheral (NLR) compartment in a series of early BC patients. NLR was not predictor of survival in our cohort. The absence of relationship between sTIL and NLR could suggest differences in the immune response in both compartments or else the need to find more accurate peripheral immune activation markers.
Fatty acid desaturase activity and single nucleotide polymorphism of fatty acid desaturase gene and breast cancer risk in estrogen receptor subtype.
Authors: Shipra Sonkusare
Journal: Journal of Clinical Oncology (2023)

e12551 Background: Breast cancer (BC) is the most common cancer in women. Various mechanisms are known to promote tumourogenesis. Arachidonic acid and its metabolites are one such pathway which promote tumorigenesis by inflammation and angiogenesis. It can be hypothesized that fatty acid metabolism is dysregulated in women with BC. We compared the fatty acid desaturases activity in women with BC and the control women. Breast cancer, which is a diet-related inflammatory disease, is also associated with the plasma concentration of omega fatty acids (n-3 and n-6), and can have an impact of its genetic variants. We studied the association between genetic variant rs174537 of fatty acid desaturase gene 1(FADS 1) and the estrogen receptor positive BC. Methods: Sixty women diagnosed with BC and 40 control women without BC between the age group of 25-60years of age were recruited for comparing the fatty acid desaturases activity. The tumors were classified by Estrogen Receptor (ER) status. Fatty acid Desaturases activities (D5, D6 and D9) were estimated as the ratio of product to precursor of individual fatty acids in plasma lipids. To study the association between genetic variant rs174537 of fatty acid desaturase gene 1(FADS 1) and the estrogen receptor positive BC, we recruited 102 (ER +ve, n = 53; ER -ve,n = 49) women with proven BC, prior to therapy. SNP rs 174537(G &gt; T) showed maximum variability and the strongest genetic determinant in the Genome-wide association study were genotyped using Sanger sequencing. Results: Decreased levels of delta 5 and delta 9 desaturases activity and increased delta 6 desaturase activity were associated with the adverse profile of BC than the control group. Estrogen Receptor status also showed variation in desaturase activity. The highest tertile of Alphalinolenic acid (ALA) showed a significantly reduced association with BC compared to the lowest tertile (OR = 0.2, 95 %CL = 0.1–1.14, P = 0.03). Median values of ALA were higher in GT/TT genotype in ER +ve molecular subtype (P = 0.03) and Docosapentaenoic acid (DPA) was higher in GG genotype of ER -ve molecular subtype (P = 0.037). When both the groups were put together the highest tertile of GG tertile showed significantly reduced association with BC compared with the other lowest tertiles of GG and GT/TT genotypes (OR, 95% CL = 0.45(0.2–0.9). Conclusions: We conclude that unbalanced polyunsaturated fatty acids and impaired fatty acid desaturation plays a role in the pathogenesis of BC. The high levels of arachidonic acid and low levels of n-3 fatty acids result in a pro-inflammatory milieu which might contribute to the pathogenesis of BC. We also conclude that the individuals with genetically determined lower activity of FADS1 (minor allele T) will derive greater advantage from n-3 fatty acids than those with higher FADS1 activity (G allele).
Deep learning-based prediction model for predicting the tumor origin of cancers of unknown primary.
Authors: Lan Lan, Yuman Zhang, Xing Li, Kai Wang
Journal: Journal of Clinical Oncology (2023)

e13562 Background: Identifying the origin of tumors is important for the treatment and prognosis of cancer patients. Despite of routine examinations including medical history, laboratory tests, histopathological assessments and imaging, 3-5% of metastatic cancers are diagnosed with cancers of unknown primary (CUP). In clinical practice, the management of CUP is challenging and empirical chemotherapy remains to be the main treatment option, leading to poor prognosis. Methods: To predict the tumor origin, we built a weighted ensemble model by Automated machine learning (autoML), including 13 models, using molecular and clinical datasets consisted of 22,018 patients and 28tumor types. The tumor type of each patient was confirmed by at least 3 pathologists. Our molecular and clinical datasets contained 7 features including age, tumor site, gene alteration, tumor mutation burden (TMB), microsatellite instability (MSI), etc. Features selected by AutoML were used to train the diagnostic model by using algorithms including CatBoost, ExtraTreesEntr (Extremely randomized trees), ExtraTreesGini, KNeighborsDist, KNeighborsUnif, LightGBM, XGBoost, etc. The best model was selected by autoML. We then optimized the model parameters and developed a No-Bias algorithm to ensure that the trained model can output "fair and unbiased" prediction results even when the input dataset had an uneven distribution in the number of cases for each cancer type. 5-fold cross validation was used to estimate the accuracy of the diagnostic models. Moreover, we validated the accuracy of diagnostic model using an independent validation set of 1,636 patients covering 28 tumor types. Results: Our model outputs the most confidently predicted tumor types in the form of TOP N (N=1-5). In the training set, the accuracy of TOP1, TOP3, and TOP5 of our diagnostic model was 72.8%, 88.4%, and 93.3%, respectively. had been successfully applied to support the diagnosis of 10 CUP patients. In one patient who was predicted to have esophageal squamous cell carcinoma, immune checkpoint inhibitor combined with chemotherapy regimen was given and achieved a 9-mouths PFS. Conclusions: We successfully developed a deep learning-based diagnostic model for predicting tumor origin with genomic and clinical data. The model could be applied to improve the clinical diagnosis of CUP patients and guide the treatment decision according to the predicted tumor origin.